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CRC 901 – On-The-Fly Computing (OTF Computing) Show image information

CRC 901 – On-The-Fly Computing (OTF Computing)

Wednesday, 02.06.2021 | 16.00 Uhr - 17.00 Uhr

Third SFB 901 Seminar in summer semester 2021

On June 2, 2021, the 3rd SFB 901 seminar in the summer semester will take place.

4:00 - 4:25 subproject B2
Speaker: Prof. Dr. Axel-Cyrille Ngonga Ngomo
Title: Question Answering on Knowledge Graphs

Abstract:
You have probably used a knowledge graph today, potentially unknowingly. Knowledge graphs have become of the most ubiquitous means to structure data by virtue of their flexibility in terms of data and schema alteration and of their expressiveness. The popularity of knowledge graphs has also led to a plethora of question answering systems being developed with the aim of answering (multi-hop) question over knowledge graphs or over knowledge graphs and other data sources such as text. In this presentation, we begin by giving an introduction to knowledge graphs. We then present some standard approaches for question answering over knowledge graphs including pipelines and end-to-end systems. Finally, we present some of the current developments in the area of question answering over knowledge graphs.  

 

4:25 - 4:50 subproject B2
Speaker: Kevin Dreßler
Title: Composing Enrichment Pipelines with Multi Expression Programming and Semantic Genetic Operators

Abstract:

The creation of knowledge graphs for particular applications can be commonly described as a directed acyclic graph (called an enrichment graph) of specialized operators on KG, such as ontology matching, link discovery and named entity recognition, operating on heterogeneous data sources. The components in enrichment graphs often require extensive configuration to lead to satisfactory results. Moreover, the set of possible operators is constantly evolving as new methods and algorithms are published.

We address the problem of learning enrichment graphs in a supervised setting as a generic automatic configuration problem of blackbox operators arranged in a DAG. We introduce an efficient supervised algorithm based on multi-expression learning for learning enrichment graphs of arbitrary size, which we aim to port to question answering systems within B2. We also discuss how this approach can be refined so as to configurate question answering systems within an online setting.

 

The talks will be held via BigBlueButton.

The University for the Information Society